In a variety of clinical situations, it is important to measure certain chemical characteristics of the patient's blood, such as pH, hematocrit, the ion concentration of calcium, potassium, chloride, sodium, glucose, lactate, creatinine, creatine, urea, the partial pressure of O2, and/or CO2, and the like. These situations range from a routine visit of a patient to a physician's office to the monitoring of a patient during open-heart surgery. Further, the required speed, accuracy, and other performance characteristics of such measurements vary with each situation.
Electrochemical sensor systems such as those described in U.S. Ser. No. 09/549,968, U.S. Ser. No. 09/872,247, U.S. Ser. No. 09/871,885, and U.S. Ser. No. 09/872,240, the entire disclosure of each incorporated by reference herein, are typically used to provide this blood-chemistry analysis on a patient's blood. Conventional sensor systems are either stand-alone machines or machines that connect to an extracorporeal shunt. Alternatively, these sensors can also connect to an ex vivo blood source, such as a heart/lung machine. To obtain a blood sample from a heart/lung machine, for example, small test samples of blood can be diverted off-line from either the venous or arterial flow lines of the heart/lung machine to a bank of micro-electrodes of the electrochemical sensor system.
Conventional micro-electrodes generate electrical signals proportional to chemical characteristics of the blood sample. To generate these electrical signals, the sensor systems may combine a chemical or biochemical recognition component (e.g., an enzyme) with a physical transducer such as a platinum electrode. Traditional chemical or biochemical recognition components selectively interact with an analyte of interest to generate, directly or indirectly, the needed electrical signal through the transducer.
The selectivity of certain biochemical recognition components makes it possible for electrochemical sensors to accurately detect certain biological analytes, even in a complex analyte mixture such as blood. Despite the high degree of selectivity of these sensors, the accuracy of such sensors depends on keeping the sensors calibrated at all times. One technique used to monitor sensor calibration is to manually verify the calibration of the sensor using an external verification solution. This technique, however, is often labor-intensive, as it is typically performed several times a day. Further, the delay between the manual verifications of the sensor may prevent a timely discovery of an uncalibrated sensor.
Another method used to monitor sensor calibration is to monitor the sensor with an external verification solution automatically at set time intervals, such as every 8 hours. Although not as labor-intensive as manually verifying a sensor, this technique may instead make it difficult to detect errors in a timely fashion, thereby enabling inaccurate readings from the sensor if it becomes uncalibrated before the scheduled verification (and correction) time. Further, automatic monitoring methods may not detect a small fraction of uncalibrated sensors. This gap in sensitivity of the automatic monitoring methods may result in uncalibrated sensors not receiving the needed corrective actions.